{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "MPuSIHgB3Vmg"
      },
      "outputs": [],
      "source": [
        "import json\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import calendar\n",
        "from google.colab import drive\n",
        "import requests"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = []"
      ],
      "metadata": {
        "id": "moHzID_A5SaX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(1, 5):\n",
        "    file_path = f'project_with_commits_{i}.json'\n",
        "    with open(file_path, 'r') as file:\n",
        "        data.extend(json.load(file))\n",
        "\n",
        "with open('combined.json', 'w') as file:\n",
        "    json.dump(data, file)\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "dpHg7XPr4_GM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "with open('combined.json', 'r') as file:\n",
        "    data = json.load(file)\n",
        "\n"
      ],
      "metadata": {
        "id": "GKGwDsr15GB8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame(data)\n",
        "\n",
        "print(df)"
      ],
      "metadata": {
        "id": "0FURnxCh5VkA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fb894f1f-3580-47d0-ae51-58f3a88ab09f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "      id                                        description  \\\n",
            "0    501                                                      \n",
            "1    510                                                      \n",
            "2    491                                                      \n",
            "3    508                                                      \n",
            "4    497                                                      \n",
            "..   ...                                                ...   \n",
            "370   14                                                      \n",
            "371   10                  Репозиторий для системы Metrikano   \n",
            "372    5                                                      \n",
            "373    2  Clone from GitHub: https://github.com/agalimul...   \n",
            "374    1                                                      \n",
            "\n",
            "                      name                                name_with_namespace  \\\n",
            "0                  Scaboom                             Maxim Gunbin / Scaboom   \n",
            "1           Scaboom.Client                      Maxim Gunbin / Scaboom.Client   \n",
            "2          voice_assistant  Сюняков Роман Русланович RRSjunyakov / voice_a...   \n",
            "3    voice_assistant_front  Сюняков Роман Русланович RRSjunyakov / voice_a...   \n",
            "4                offigator  Шарафутдинов Карим Маратович KMSharafutdinov /...   \n",
            "..                     ...                                                ...   \n",
            "370                diploma                                  Dmitrij / diploma   \n",
            "371              metrikano            Романов Андрей Владимирович / metrikano   \n",
            "372       Course_work_2018                            Nina / Course_work_2018   \n",
            "373             taiga-back                          Nikita Rusin / taiga-back   \n",
            "374            taiga-front                         Nikita Rusin / taiga-front   \n",
            "\n",
            "                      path                path_with_namespace  \\\n",
            "0                  Scaboom                   MVGunbin/Scaboom   \n",
            "1           Scaboom.Client            MVGunbin/Scaboom.Client   \n",
            "2          voice_assistant        RRSjunyakov/voice_assistant   \n",
            "3    voice_assistant_front  RRSjunyakov/voice_assistant_front   \n",
            "4                offigator          KMSharafutdinov/offigator   \n",
            "..                     ...                                ...   \n",
            "370                diploma                DmSFilippov/diploma   \n",
            "371              metrikano                Romanidze/metrikano   \n",
            "372       Course_work_2018        NRFazlyeva/Course_work_2018   \n",
            "373             taiga-back                nikrusin/taiga-back   \n",
            "374            taiga-front               nikrusin/taiga-front   \n",
            "\n",
            "                   created_at default_branch tag_list  \\\n",
            "0    2022-06-22T03:37:52.080Z         master       []   \n",
            "1    2022-06-29T05:06:43.195Z         master       []   \n",
            "2    2022-06-16T13:18:58.549Z            dev       []   \n",
            "3    2022-06-27T07:23:36.185Z         master       []   \n",
            "4    2022-06-19T22:34:19.013Z           main       []   \n",
            "..                        ...            ...      ...   \n",
            "370  2019-05-15T09:05:12.372Z         master       []   \n",
            "371  2019-05-15T06:27:10.850Z         master       []   \n",
            "372  2018-11-28T02:31:44.473Z         master       []   \n",
            "373  2018-10-20T13:20:12.562Z         master       []   \n",
            "374  2018-10-20T13:16:48.533Z         master       []   \n",
            "\n",
            "                                       ssh_url_to_repo  ... public_jobs  \\\n",
            "0             git@gititis.kpfu.ru:MVGunbin/Scaboom.git  ...        True   \n",
            "1      git@gititis.kpfu.ru:MVGunbin/Scaboom.Client.git  ...        True   \n",
            "2    git@gititis.kpfu.ru:RRSjunyakov/voice_assistan...  ...        True   \n",
            "3    git@gititis.kpfu.ru:RRSjunyakov/voice_assistan...  ...        True   \n",
            "4    git@gititis.kpfu.ru:KMSharafutdinov/offigator.git  ...        True   \n",
            "..                                                 ...  ...         ...   \n",
            "370        git@gititis.kpfu.ru:DmSFilippov/diploma.git  ...        True   \n",
            "371        git@gititis.kpfu.ru:Romanidze/metrikano.git  ...        True   \n",
            "372  git@gititis.kpfu.ru:NRFazlyeva/Course_work_201...  ...        True   \n",
            "373        git@gititis.kpfu.ru:nikrusin/taiga-back.git  ...        True   \n",
            "374       git@gititis.kpfu.ru:nikrusin/taiga-front.git  ...        True   \n",
            "\n",
            "    ci_config_path shared_with_groups  only_allow_merge_if_pipeline_succeeds  \\\n",
            "0             None                 []                                  False   \n",
            "1             None                 []                                  False   \n",
            "2             None                 []                                  False   \n",
            "3             None                 []                                  False   \n",
            "4             None                 []                                  False   \n",
            "..             ...                ...                                    ...   \n",
            "370           None                 []                                  False   \n",
            "371           None                 []                                  False   \n",
            "372           None                 []                                  False   \n",
            "373           None                 []                                  False   \n",
            "374           None                 []                                  False   \n",
            "\n",
            "     request_access_enabled only_allow_merge_if_all_discussions_are_resolved  \\\n",
            "0                     False                                            False   \n",
            "1                     False                                            False   \n",
            "2                     False                                            False   \n",
            "3                     False                                            False   \n",
            "4                     False                                            False   \n",
            "..                      ...                                              ...   \n",
            "370                   False                                            False   \n",
            "371                   False                                            False   \n",
            "372                   False                                            False   \n",
            "373                   False                                            False   \n",
            "374                   False                                            False   \n",
            "\n",
            "    printing_merge_request_link_enabled  merge_method  \\\n",
            "0                                  True         merge   \n",
            "1                                  True         merge   \n",
            "2                                  True         merge   \n",
            "3                                  True         merge   \n",
            "4                                  True         merge   \n",
            "..                                  ...           ...   \n",
            "370                                True         merge   \n",
            "371                                True         merge   \n",
            "372                                True         merge   \n",
            "373                                True         merge   \n",
            "374                                True         merge   \n",
            "\n",
            "                                            statistics  \\\n",
            "0    {'commit_count': 56, 'storage_size': 503316, '...   \n",
            "1    {'commit_count': 8, 'storage_size': 775946, 'r...   \n",
            "2    {'commit_count': 11, 'storage_size': 660602, '...   \n",
            "3    {'commit_count': 2, 'storage_size': 1719664, '...   \n",
            "4    {'commit_count': 1, 'storage_size': 6197084, '...   \n",
            "..                                                 ...   \n",
            "370  {'commit_count': 1, 'storage_size': 21621637, ...   \n",
            "371  {'commit_count': 1, 'storage_size': 1646264, '...   \n",
            "372  {'commit_count': 1, 'storage_size': 1499463, '...   \n",
            "373  {'commit_count': 3542, 'storage_size': 1845493...   \n",
            "374  {'commit_count': 5302, 'storage_size': 4100980...   \n",
            "\n",
            "                                        permissions  \n",
            "0    {'project_access': None, 'group_access': None}  \n",
            "1    {'project_access': None, 'group_access': None}  \n",
            "2    {'project_access': None, 'group_access': None}  \n",
            "3    {'project_access': None, 'group_access': None}  \n",
            "4    {'project_access': None, 'group_access': None}  \n",
            "..                                              ...  \n",
            "370  {'project_access': None, 'group_access': None}  \n",
            "371  {'project_access': None, 'group_access': None}  \n",
            "372  {'project_access': None, 'group_access': None}  \n",
            "373  {'project_access': None, 'group_access': None}  \n",
            "374  {'project_access': None, 'group_access': None}  \n",
            "\n",
            "[375 rows x 43 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "columns_to_keep = ['id', 'name', 'created_at', 'star_count','forks_count','last_activity_at','visibility','statistics', 'description']"
      ],
      "metadata": {
        "id": "Libkp8Wj6Kyc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.drop(columns=df.columns.difference(columns_to_keep), axis=1)"
      ],
      "metadata": {
        "id": "LLTmw8vK8Wtx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yQisTqSW8S_r",
        "outputId": "aad254ba-3878-4db4-e69f-101bd2fc1099"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "      id                                        description  \\\n",
            "0    501                                                      \n",
            "1    510                                                      \n",
            "2    491                                                      \n",
            "3    508                                                      \n",
            "4    497                                                      \n",
            "..   ...                                                ...   \n",
            "370   14                                                      \n",
            "371   10                  Репозиторий для системы Metrikano   \n",
            "372    5                                                      \n",
            "373    2  Clone from GitHub: https://github.com/agalimul...   \n",
            "374    1                                                      \n",
            "\n",
            "                      name                created_at  star_count  forks_count  \\\n",
            "0                  Scaboom  2022-06-22T03:37:52.080Z           0            0   \n",
            "1           Scaboom.Client  2022-06-29T05:06:43.195Z           0            0   \n",
            "2          voice_assistant  2022-06-16T13:18:58.549Z           0            0   \n",
            "3    voice_assistant_front  2022-06-27T07:23:36.185Z           0            0   \n",
            "4                offigator  2022-06-19T22:34:19.013Z           0            0   \n",
            "..                     ...                       ...         ...          ...   \n",
            "370                diploma  2019-05-15T09:05:12.372Z           0            0   \n",
            "371              metrikano  2019-05-15T06:27:10.850Z           0            0   \n",
            "372       Course_work_2018  2018-11-28T02:31:44.473Z           0            0   \n",
            "373             taiga-back  2018-10-20T13:20:12.562Z           0            0   \n",
            "374            taiga-front  2018-10-20T13:16:48.533Z           0            0   \n",
            "\n",
            "             last_activity_at visibility  \\\n",
            "0    2022-06-29T05:11:19.677Z   internal   \n",
            "1    2022-06-29T05:06:43.195Z   internal   \n",
            "2    2022-06-27T07:27:26.436Z     public   \n",
            "3    2022-06-27T07:23:36.185Z     public   \n",
            "4    2022-06-27T05:07:57.602Z     public   \n",
            "..                        ...        ...   \n",
            "370  2019-05-15T09:05:12.372Z     public   \n",
            "371  2019-05-15T06:27:10.850Z     public   \n",
            "372  2018-11-28T02:31:44.473Z     public   \n",
            "373  2018-10-20T13:20:12.562Z   internal   \n",
            "374  2018-10-20T13:16:48.533Z   internal   \n",
            "\n",
            "                                            statistics  \n",
            "0    {'commit_count': 56, 'storage_size': 503316, '...  \n",
            "1    {'commit_count': 8, 'storage_size': 775946, 'r...  \n",
            "2    {'commit_count': 11, 'storage_size': 660602, '...  \n",
            "3    {'commit_count': 2, 'storage_size': 1719664, '...  \n",
            "4    {'commit_count': 1, 'storage_size': 6197084, '...  \n",
            "..                                                 ...  \n",
            "370  {'commit_count': 1, 'storage_size': 21621637, ...  \n",
            "371  {'commit_count': 1, 'storage_size': 1646264, '...  \n",
            "372  {'commit_count': 1, 'storage_size': 1499463, '...  \n",
            "373  {'commit_count': 3542, 'storage_size': 1845493...  \n",
            "374  {'commit_count': 5302, 'storage_size': 4100980...  \n",
            "\n",
            "[375 rows x 9 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['created_at'] = pd.to_datetime(df['created_at'])\n",
        "\n",
        "df['year_created'] = df['created_at'].dt.year\n",
        "\n",
        "projects_per_year = df['year_created'].value_counts().sort_index()\n",
        "\n"
      ],
      "metadata": {
        "id": "IH4Rl6jI7YPe"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10, 6))\n",
        "projects_per_year.plot(kind='bar', color='skyblue')\n",
        "plt.title('Number of Projects Created Each Year')\n",
        "plt.xlabel('Year')\n",
        "plt.ylabel('Number of Projects')\n",
        "plt.grid(axis='y', linestyle='--', alpha=0.6)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "4MdJRNq872X_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 585
        },
        "outputId": "6c96055a-0a1f-4117-d3c9-5e465d7ad666"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for year, count in projects_per_year.items():\n",
        "    print(f\"Year {year}: {count} projects\")"
      ],
      "metadata": {
        "id": "Q6B0u2bq8fd5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "49d54738-cc90-427d-95bc-d65af2dba564"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Year 2018: 3 projects\n",
            "Year 2019: 227 projects\n",
            "Year 2020: 101 projects\n",
            "Year 2021: 14 projects\n",
            "Year 2022: 30 projects\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**2018**"
      ],
      "metadata": {
        "id": "rLQIvmFmEtW7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_2018 = df[df['created_at'].dt.year == 2018]\n",
        "\n",
        "df_2018['month_created'] = df_2018['created_at'].dt.month"
      ],
      "metadata": {
        "id": "4bGl8-GOAIvl",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c4f722e8-fe4c-4339-b1a4-1f43b1c8a78c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-13-31ff91e3f4d5>:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  df_2018['month_created'] = df_2018['created_at'].dt.month\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_2018['month_created'] = df_2018['created_at'].dt.month\n",
        "\n",
        "projects_per_month = df_2018['month_created'].value_counts().sort_index()\n",
        "\n",
        "plt.figure(figsize=(10, 6))\n",
        "projects_per_month.plot(kind='bar', color='skyblue')\n",
        "plt.title('Number of Projects Created Each Month in 2018')\n",
        "plt.xlabel('Month')\n",
        "plt.ylabel('Number of Projects')\n",
        "plt.yticks(range(0, max(projects_per_month)+1, 2))\n",
        "plt.xticks(range(0, 12), ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'])\n",
        "\n",
        "plt.grid(axis='y', linestyle='--', alpha=0.6)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "J2DP1PlY9kOh",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 683
        },
        "outputId": "00a06351-6652-4bd3-d753-9eafbe5c4392"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-14-547febe2b121>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  df_2018['month_created'] = df_2018['created_at'].dt.month\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**2019**"
      ],
      "metadata": {
        "id": "-7YMj4ZmEpor"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_2019 = df[df['created_at'].dt.year == 2019]\n",
        "\n",
        "df_2019['month_created'] = df_2019['created_at'].dt.month\n",
        "\n",
        "projects_per_month = df_2019['month_created'].value_counts().sort_index()\n"
      ],
      "metadata": {
        "id": "4xOm4i6V_9VA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b34225e2-7bf4-4be6-fd12-90d43771d239"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-15-697874a865a7>:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  df_2019['month_created'] = df_2019['created_at'].dt.month\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10, 6))\n",
        "bar_plot = projects_per_month.plot(kind='bar', color='skyblue')\n",
        "plt.title('Number of Projects Created Each Month in 2019')\n",
        "plt.xlabel('Month')\n",
        "plt.ylabel('Number of Projects')\n",
        "\n",
        "for i, v in enumerate(projects_per_month):\n",
        "    plt.text(i, v + 0.2, str(v), ha='center')\n",
        "\n",
        "plt.xticks(range(0, 12), [calendar.month_name[i] for i in range(1, 13)])\n",
        "plt.grid(axis='y', linestyle='--', alpha=0.6)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "ppI_OHqlCJ4J",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 627
        },
        "outputId": "19bae9f9-f449-4460-a117-81515bc39137"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**2020**"
      ],
      "metadata": {
        "id": "22iAQFRzEgYO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_2020 = df[df['created_at'].dt.year == 2020]\n",
        "\n",
        "df_2020['month_created'] = df_2020['created_at'].dt.month\n",
        "\n",
        "projects_per_month = df_2020['month_created'].value_counts().sort_index()\n",
        "\n",
        "plt.figure(figsize=(10, 6))\n",
        "bar_plot = projects_per_month.plot(kind='bar', color='skyblue')\n",
        "plt.title('Number of Projects Created Each Month in 2020')\n",
        "plt.xlabel('Month')\n",
        "plt.ylabel('Number of Projects')\n",
        "\n",
        "for i, v in enumerate(projects_per_month):\n",
        "    plt.text(i, v + 0.2, str(v), ha='center')\n",
        "\n",
        "plt.xticks(range(0, 12), [calendar.month_name[i] for i in range(1, 13)])\n",
        "plt.grid(axis='y', linestyle='--', alpha=0.6)\n",
        "plt.show()\n"
      ],
      "metadata": {
        "id": "lqmjqk0DEGJL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 731
        },
        "outputId": "0278a6d4-7e8e-4820-fcca-072c76f05000"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-17-350da5844c92>:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  df_2020['month_created'] = df_2020['created_at'].dt.month\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "коммиты"
      ],
      "metadata": {
        "id": "SAYK1holGDrg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "projects = {}\n",
        "\n",
        "for project in data:\n",
        "\n",
        "    project_data = {\n",
        "        'name': project['name'],\n",
        "        'commits': project['statistics']['commit_count']\n",
        "    }\n",
        "\n",
        "    projects[project_data['name']] = project_data['commits']\n",
        "\n",
        "\n",
        "sorted_projects = sorted(projects.items(), key=lambda x: x[1], reverse=True)\n",
        "\n",
        "for project, commits in sorted_projects:\n",
        "    print(f'{project}: {commits}')"
      ],
      "metadata": {
        "id": "oqQEmRd4GDFk",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7f98f4e0-7dcc-4a26-d6ab-e429478a5107"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "taiga-front: 5302\n",
            "taiga-back: 3542\n",
            "scientometric-indicators: 1342\n",
            "neomodel: 1118\n",
            "graphql-core: 862\n",
            "graphene-neo4j: 671\n",
            "AnimationUnity: 637\n",
            "VASILYEV_VKR_LIRS: 275\n",
            "master-thesis: 256\n",
            "distribution: 219\n",
            "core: 171\n",
            "robot-lawyer: 161\n",
            "profile-frontend: 126\n",
            "visportraits_server: 109\n",
            "microsimulator-gazebo: 107\n",
            "FullTextSearch: 91\n",
            "visportraits_plugin: 88\n",
            "Unity3DAutoTestFramework: 83\n",
            "sentiment-nn: 77\n",
            "thesis: 64\n",
            "Defectoscoper: 62\n",
            "ARSDK: 62\n",
            "arsdk: 57\n",
            "Join: 57\n",
            "Scaboom: 56\n",
            "ansible-configs: 56\n",
            "study_insight: 50\n",
            "big-data-lms-back-end: 49\n",
            "diploma-backend: 43\n",
            "visportraits_framework: 43\n",
            "engineer-remote-control-gui: 39\n",
            "passmanager: 37\n",
            "big-data-lms-front-end: 33\n",
            "edu-text-checker-practise: 32\n",
            "EasyXML: 31\n",
            "HistoryQuiz: 31\n",
            "rpd-analyzer: 27\n",
            "duplicate_finder: 26\n",
            "Zalyalutdinov-2019: 25\n",
            "text-analyzer-tool: 23\n",
            "micromock: 22\n",
            "CloadRestAPIServicesGeneration: 21\n",
            "EmoVideo-thesis: 20\n",
            "user-service: 20\n",
            "metrics-identification-platform: 19\n",
            "kpfu-ovpn-gateway: 19\n",
            "iarma: 17\n",
            "FlexCodeGeneration: 17\n",
            "BookCatalogue: 17\n",
            "diplomProject: 14\n",
            "UIGenByXML: 14\n",
            "VKR_KSChernysheva: 13\n",
            "vk_thesis: 13\n",
            "ci_cd-methodic-manual: 13\n",
            "diplomnaya_rabota: 12\n",
            "formulaSearch: 12\n",
            "PhotoTurntable: 12\n",
            "voice_assistant: 11\n",
            "Chebotareva_VKR_LIRS: 11\n",
            "tour-service: 11\n",
            "visportraits_analyzer_service: 10\n",
            "nginx-logs-calculator: 10\n",
            "brexit-news-topic-modeling-comprassion: 10\n",
            "Master_Thesis_2019: 10\n",
            "automation_system: 9\n",
            "MasterWork: 9\n",
            "mail-sender-service: 9\n",
            "Scaboom.Client: 8\n",
            "diploma-eclipse-plugin: 8\n",
            "gamification_platform_for_exams: 8\n",
            "BookCatalogueJavaFX: 8\n",
            "vault-generator: 7\n",
            "FlutterBuilder: 7\n",
            "automation-system: 7\n",
            "recycling-app: 6\n",
            "Bachelor-graduation-project: 6\n",
            "StateFlowFramework: 6\n",
            "Diplom2019: 6\n",
            "Dobrokvashina-2019: 6\n",
            "mammalian-vocalisation-synthesis: 6\n",
            "flutter-starter-plugin: 5\n",
            "Autoencoder: 5\n",
            "code-quality-analyzers: 5\n",
            "django-cdbms: 5\n",
            "media_data_analysis: 5\n",
            "SaaSAutoTest: 5\n",
            "MathFS: 5\n",
            "NaturalDisasterSimulator: 5\n",
            "law_dsl: 5\n",
            "data-pipeline-vkr2022: 4\n",
            "VKR: 4\n",
            "VKR_VABezrukov: 4\n",
            "B_VKR: 4\n",
            "VKR-Gabbasova-11821: 4\n",
            "VKR-Fedyushkin-11-606: 4\n",
            "Lukyanov_Bachelor_Thesis: 4\n",
            "diploma-work-malikov: 4\n",
            "city-comm-diploma: 4\n",
            "P2PCrowdLanding: 4\n",
            "cdc_demo_project: 4\n",
            "Kostyuchenko-2019: 4\n",
            "multithreaded-sequence-recovery: 4\n",
            "VKR_GuISharafutdinova: 3\n",
            "Scenario-Editor-2020: 3\n",
            "diplom: 3\n",
            "Named Entity Recognition: 3\n",
            "projects-datastorage: 3\n",
            "DIPLOMA_OLDEST: 3\n",
            "university-resources: 3\n",
            "frontend-microservices-framework: 3\n",
            "DepressionPredictionUsingSocialMediaPosts: 3\n",
            "NER: 3\n",
            "competitions_constructor: 3\n",
            "Heterogeneous-robots-protocols: 3\n",
            "SimulateWeightVR: 3\n",
            "rsjr: 3\n",
            "AI_via_Neural_Networks: 3\n",
            "SemanticTest: 3\n",
            "my-awesome-diplom: 3\n",
            "engineer_server: 3\n",
            "DrinkQualityDeterminator: 3\n",
            "voice_assistant_front: 2\n",
            "Diploma: 2\n",
            "MLOpsPipeline: 2\n",
            "TMA: 2\n",
            "student-assistant: 2\n",
            "diploma-intellij-idea-plugin: 2\n",
            "github-sampler: 2\n",
            "monoslam: 2\n",
            "vkr_paraviewpylib: 2\n",
            "Diplom: 2\n",
            "abpass: 2\n",
            "grad-project: 2\n",
            "OpenApiTester: 2\n",
            "ForceTemplate: 2\n",
            "Warehouse: 2\n",
            "colour_video_cat: 2\n",
            "product-analysis-system: 2\n",
            "DIPLOMA_OLD: 2\n",
            "MapEditor: 2\n",
            "taiga-mobile-app: 2\n",
            "similar-theme-document-finder: 2\n",
            "kurs2: 2\n",
            "DBaaS: 2\n",
            "AutomaticDesignSystem: 2\n",
            "XcodeAutoConfiguration: 2\n",
            "apm: 2\n",
            "rs: 2\n",
            "itis-xqueue-watcher: 2\n",
            "infographics: 2\n",
            "zadacha-o-razvozke: 2\n",
            "coursework_2course: 2\n",
            "DipWork: 2\n",
            "3D_gn_zvuk_diploma: 2\n",
            "AutoTesting: 2\n",
            "Schedule: 2\n",
            "analyzer-photos-by-planograms: 2\n",
            "Elib_FilTA: 2\n",
            "gfiskandarova-diplom: 2\n",
            "OTP: 2\n",
            "graduate-work: 2\n",
            "highload-testing-app: 2\n",
            "GamingPrototypeGenerator: 2\n",
            "LUT_Table_utility: 2\n",
            "ui_detection: 2\n",
            "course-work-bedrin-11-605: 2\n",
            "upmjs: 2\n",
            "LawDocClassificatorApp: 2\n",
            "BKP-Hayrullin-11504: 2\n",
            "figma-plugin: 2\n",
            "adaptive-testing-system: 2\n",
            "VideoCategorization: 2\n",
            "Presenter: 2\n",
            "project_architecture_generation: 2\n",
            "Lightning_Network: 2\n",
            "FormulaSearch: 2\n",
            "JavaWarrior: 2\n",
            "TicketRecognizer: 2\n",
            "MweExtraction: 2\n",
            "Semester4: 2\n",
            "mail-writing-service: 2\n",
            "offigator: 1\n",
            "thesis_project_2022: 1\n",
            "dtc-server: 1\n",
            "dtc-runner: 1\n",
            "dtc-front: 1\n",
            "dtc-core: 1\n",
            "Text2SceneGenerator: 1\n",
            "ui-converter: 1\n",
            "city-modelling: 1\n",
            "cloud-office: 1\n",
            "VKR_Kuzmin_11-803: 1\n",
            "VKR_Arsembekova_11-803: 1\n",
            "DoiRegistrar: 1\n",
            "method_of_group_accounting_of_arguments: 1\n",
            "VKR_AYUArsenyuk: 1\n",
            "VKR_KVKolyshkin: 1\n",
            "VKR_PSNovoselov: 1\n",
            "VKR_RMMusin: 1\n",
            "AR-Barcode-Scanner: 1\n",
            "VKR_ARKhamedzhanov: 1\n",
            "VKR_VVPetrov: 1\n",
            "VKR_ASHusnutdinov: 1\n",
            "VKR_TMBadretdinov: 1\n",
            "VKR_AdRGarifullina: 1\n",
            "vkr_the_supplier: 1\n",
            "lambda: 1\n",
            "robustness: 1\n",
            "DetectionObject: 1\n",
            "Hand_in_VR: 1\n",
            "Demo_project: 1\n",
            "Demo: 1\n",
            "roc_analysis: 1\n",
            "diploma: 1\n",
            "bachelor_thesis: 1\n",
            "depression-detection-system: 1\n",
            "thesis_project_2020: 1\n",
            "RAClassifier: 1\n",
            "DynamicApps: 1\n",
            "prove: 1\n",
            "VKR_Vorobyova_11-821: 1\n",
            "classifier-sustainability: 1\n",
            "VKR_TEST_SERVER: 1\n",
            "VKR_TEST_CLIENT: 1\n",
            "VR_HandControl: 1\n",
            "OTRS_CLASSIF: 1\n",
            "VKR_LIB: 1\n",
            "CreatorDocument: 1\n",
            "2020Diploma: 1\n",
            "PK: 1\n",
            "RecSystem: 1\n",
            "gtn: 1\n",
            "diploma2020: 1\n",
            "generate_android_project_plugin: 1\n",
            "digital-portrait: 1\n",
            "ux-generator: 1\n",
            "sentiment-analysis: 1\n",
            "graphql-security-java: 1\n",
            "diploma-work: 1\n",
            "database-obfuscation: 1\n",
            "DATA: 1\n",
            "diploma-gtms: 1\n",
            "diploma-pasc: 1\n",
            "qa-chat: 1\n",
            "social-simulation: 1\n",
            "VKR-Astafev-11607: 1\n",
            "bim-parser: 1\n",
            "taiga-media: 1\n",
            "Technological-implementation-of-mobile-learning-method-for-project-manager-preparation: 1\n",
            "gamefication-module: 1\n",
            "Developing_an_express_project_management_methodology_for_creating_computer_games_based_on_a_flexible_approach: 1\n",
            "vkr2019: 1\n",
            "master_thesis_smart_museum: 1\n",
            "OrganicLiquidsVis: 1\n",
            "VKR-Gazizov-11712: 1\n",
            "IndividualEduTrajectories: 1\n",
            "high_school_rank_system: 1\n",
            "WireframeRecognition: 1\n",
            "component_detection: 1\n",
            "comparison_of_tables: 1\n",
            "mobile_map: 1\n",
            "ExampleTask: 1\n",
            "CryptoCloudAPI: 1\n",
            "CardReader: 1\n",
            "medicine-semestr-project: 1\n",
            "bachelor-thesis: 1\n",
            "timetable_agent: 1\n",
            "students_distribution: 1\n",
            "ROBULAPath: 1\n",
            "SpringBootProjectsGenerator: 1\n",
            "tunnel-car-wash-app: 1\n",
            "ms-creator: 1\n",
            "CarCrashDetection: 1\n",
            "VKRMaketKFU: 1\n",
            "StoryMechanicsGeneration: 1\n",
            "FINAL-QUALIFICATION-WORK: 1\n",
            "Autotesting: 1\n",
            "qualitis: 1\n",
            "platform-for-user-testing: 1\n",
            "DiplomnayaRabota: 1\n",
            "ermolaeva: 1\n",
            "gui-setting-app-doc: 1\n",
            "gui-setting-app: 1\n",
            "VREngine: 1\n",
            "The-Development-Of-Motion-Capture-System: 1\n",
            "MathMLconvert: 1\n",
            "designing-empathy-in-virtual-worlds: 1\n",
            "NativeInterface: 1\n",
            "BankPortalAggregator: 1\n",
            "K_3: 1\n",
            "LabWork: 1\n",
            "my_course_work: 1\n",
            "course-work-3: 1\n",
            "RPG_game: 1\n",
            "iaermoshin-diplom: 1\n",
            "volumetric-cloud: 1\n",
            "vkr: 1\n",
            "RPG_Vakatov: 1\n",
            "photo-editor: 1\n",
            "3-course-work: 1\n",
            "course-work-3-semester: 1\n",
            "robots-battle: 1\n",
            "BlogProject: 1\n",
            "SmartCarSharing: 1\n",
            "VideoAnalizer: 1\n",
            "Marketplace: 1\n",
            "MusEvent: 1\n",
            "ssr-spa-app: 1\n",
            "swarm_hector_quadrotor_monoSLAM: 1\n",
            "stay-in-touch-api: 1\n",
            "JoinAndroifLab: 1\n",
            "microblog-beanPostProcessor-coursework: 1\n",
            "smart-system: 1\n",
            "NLPcourse: 1\n",
            "NLPCourseWork: 1\n",
            "CompanyPRJ: 1\n",
            "upload-files-to-selectel-cdn-with-spring: 1\n",
            "CourseWork3: 1\n",
            "films: 1\n",
            "SearchSystem: 1\n",
            "CourseWork2019: 1\n",
            "health_control_system: 1\n",
            "conditional_serializers: 1\n",
            "course-work-2019: 1\n",
            "Saitov_Azat_11-707: 1\n",
            "DigitalTwin: 1\n",
            "AnalyticalService: 1\n",
            "coursework-2019-EurekaHRBot: 1\n",
            "skills_project: 1\n",
            "Shop: 1\n",
            "Course_work: 1\n",
            "coursework: 1\n",
            "kursach: 1\n",
            "mobile_clients_side: 1\n",
            "server_side: 1\n",
            "metrikano: 1\n",
            "Course_work_2018: 1\n",
            "continuous_data_quality_vkr: 0\n",
            "neural-world-generator: 0\n",
            "instaparser: 0\n",
            "query_log_analyze_front: 0\n",
            "building_memristive_neuron: 0\n",
            "rrakhimova-diplom: 0\n",
            "MathTest: 0\n",
            "RPG-Game: 0\n",
            "QuizEngine: 0\n",
            "avrora-simulation-parking: 0\n",
            "uks-mobile: 0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "commit_ranges = {\n",
        "    '1 commit': 0,\n",
        "    '2-10 commits': 0,\n",
        "    '11-100 commits': 0,\n",
        "    'more than 100 commits': 0\n",
        "}\n",
        "\n",
        "for project in data:\n",
        "    commit_count = project['statistics']['commit_count']\n",
        "    if commit_count == 1:\n",
        "        commit_ranges['1 commit'] += 1\n",
        "    elif 2 <= commit_count <= 10:\n",
        "        commit_ranges['2-10 commits'] += 1\n",
        "    elif 11 <= commit_count <= 100:\n",
        "        commit_ranges['11-100 commits'] += 1\n",
        "    else:\n",
        "        commit_ranges['more than 100 commits'] += 1\n",
        "\n",
        "plt.figure(figsize=(8, 8))\n",
        "plt.pie(commit_ranges.values(), labels=commit_ranges.keys(), autopct='%1.1f%%', startangle=140)\n",
        "plt.axis('equal')\n",
        "plt.title('Commit Distribution in Projects')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "rMNrSBVGHD5Z",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 675
        },
        "outputId": "55d3c58b-59e5-43ca-f019-67e3418cf162"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**По имени**"
      ],
      "metadata": {
        "id": "HTxrUkPB1mrT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for project in data:\n",
        "    print(project.get('name', 'No Name'))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GDHD_y1S4ASD",
        "outputId": "3ed2813d-c88c-449e-8ade-f2df1d3ba144"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Scaboom\n",
            "Scaboom.Client\n",
            "voice_assistant\n",
            "voice_assistant_front\n",
            "offigator\n",
            "data-pipeline-vkr2022\n",
            "thesis_project_2022\n",
            "dtc-server\n",
            "dtc-runner\n",
            "dtc-front\n",
            "dtc-core\n",
            "Diploma\n",
            "Text2SceneGenerator\n",
            "recycling-app\n",
            "ui-converter\n",
            "city-modelling\n",
            "VKR\n",
            "MLOpsPipeline\n",
            "cloud-office\n",
            "continuous_data_quality_vkr\n",
            "diplomProject\n",
            "VKR_Kuzmin_11-803\n",
            "VKR_Arsembekova_11-803\n",
            "neural-world-generator\n",
            "TMA\n",
            "vault-generator\n",
            "flutter-starter-plugin\n",
            "iarma\n",
            "DoiRegistrar\n",
            "method_of_group_accounting_of_arguments\n",
            "VKR_AYUArsenyuk\n",
            "VKR_KVKolyshkin\n",
            "VKR_PSNovoselov\n",
            "VKR_RMMusin\n",
            "AR-Barcode-Scanner\n",
            "diplomnaya_rabota\n",
            "VKR_KSChernysheva\n",
            "VKR_ARKhamedzhanov\n",
            "VKR_VABezrukov\n",
            "VKR_VVPetrov\n",
            "VKR_ASHusnutdinov\n",
            "VKR_TMBadretdinov\n",
            "VKR_GuISharafutdinova\n",
            "VKR_AdRGarifullina\n",
            "vkr_the_supplier\n",
            "Autoencoder\n",
            "Chebotareva_VKR_LIRS\n",
            "Scenario-Editor-2020\n",
            "lambda\n",
            "robustness\n",
            "DetectionObject\n",
            "Hand_in_VR\n",
            "study_insight\n",
            "code-quality-analyzers\n",
            "Diploma\n",
            "student-assistant\n",
            "Demo_project\n",
            "Demo\n",
            "diploma-backend\n",
            "diplom\n",
            "diploma-eclipse-plugin\n",
            "Named Entity Recognition\n",
            "diploma-intellij-idea-plugin\n",
            "github-sampler\n",
            "roc_analysis\n",
            "diploma\n",
            "bachelor_thesis\n",
            "depression-detection-system\n",
            "thesis_project_2020\n",
            "projects-datastorage\n",
            "diploma\n",
            "Defectoscoper\n",
            "FlexCodeGeneration\n",
            "diploma\n",
            "text-analyzer-tool\n",
            "visportraits_plugin\n",
            "visportraits_framework\n",
            "visportraits_analyzer_service\n",
            "engineer-remote-control-gui\n",
            "instaparser\n",
            "visportraits_server\n",
            "RAClassifier\n",
            "DynamicApps\n",
            "monoslam\n",
            "vkr_paraviewpylib\n",
            "query_log_analyze_front\n",
            "Diplom\n",
            "metrics-identification-platform\n",
            "VKR\n",
            "prove\n",
            "Diplom\n",
            "VKR_Vorobyova_11-821\n",
            "ARSDK\n",
            "arsdk\n",
            "Bachelor-graduation-project\n",
            "B_VKR\n",
            "VKR-Gabbasova-11821\n",
            "classifier-sustainability\n",
            "abpass\n",
            "grad-project\n",
            "VKR_TEST_SERVER\n",
            "VKR_TEST_CLIENT\n",
            "VR_HandControl\n",
            "OTRS_CLASSIF\n",
            "VKR_LIB\n",
            "CreatorDocument\n",
            "OpenApiTester\n",
            "2020Diploma\n",
            "PK\n",
            "VKR-Fedyushkin-11-606\n",
            "ForceTemplate\n",
            "Warehouse\n",
            "ansible-configs\n",
            "core\n",
            "profile-frontend\n",
            "microsimulator-gazebo\n",
            "RecSystem\n",
            "big-data-lms-front-end\n",
            "big-data-lms-back-end\n",
            "Diploma\n",
            "colour_video_cat\n",
            "gtn\n",
            "diploma2020\n",
            "generate_android_project_plugin\n",
            "digital-portrait\n",
            "UIGenByXML\n",
            "ux-generator\n",
            "product-analysis-system\n",
            "sentiment-analysis\n",
            "graphql-security-java\n",
            "diploma-work\n",
            "diploma\n",
            "database-obfuscation\n",
            "DATA\n",
            "kpfu-ovpn-gateway\n",
            "diploma-gtms\n",
            "diploma\n",
            "nginx-logs-calculator\n",
            "diploma-pasc\n",
            "Unity3DAutoTestFramework\n",
            "qa-chat\n",
            "social-simulation\n",
            "Diploma\n",
            "VKR-Astafev-11607\n",
            "bim-parser\n",
            "gamification_platform_for_exams\n",
            "edu-text-checker-practise\n",
            "DIPLOMA_OLDEST\n",
            "DIPLOMA_OLD\n",
            "sentiment-nn\n",
            "MapEditor\n",
            "master-thesis\n",
            "VASILYEV_VKR_LIRS\n",
            "taiga-media\n",
            "Technological-implementation-of-mobile-learning-method-for-project-manager-preparation\n",
            "taiga-mobile-app\n",
            "gamefication-module\n",
            "similar-theme-document-finder\n",
            "kurs2\n",
            "automation_system\n",
            "Developing_an_express_project_management_methodology_for_creating_computer_games_based_on_a_flexible_approach\n",
            "vkr2019\n",
            "master_thesis_smart_museum\n",
            "OrganicLiquidsVis\n",
            "DBaaS\n",
            "VKR-Gazizov-11712\n",
            "IndividualEduTrajectories\n",
            "StateFlowFramework\n",
            "university-resources\n",
            "high_school_rank_system\n",
            "django-cdbms\n",
            "MasterWork\n",
            "AutomaticDesignSystem\n",
            "XcodeAutoConfiguration\n",
            "VKR\n",
            "diploma\n",
            "WireframeRecognition\n",
            "EasyXML\n",
            "component_detection\n",
            "Lukyanov_Bachelor_Thesis\n",
            "comparison_of_tables\n",
            "apm\n",
            "micromock\n",
            "VKR\n",
            "mobile_map\n",
            "brexit-news-topic-modeling-comprassion\n",
            "frontend-microservices-framework\n",
            "rs\n",
            "ExampleTask\n",
            "itis-xqueue-watcher\n",
            "diplom\n",
            "DepressionPredictionUsingSocialMediaPosts\n",
            "NER\n",
            "infographics\n",
            "FlutterBuilder\n",
            "CryptoCloudAPI\n",
            "CardReader\n",
            "medicine-semestr-project\n",
            "competitions_constructor\n",
            "diploma\n",
            "media_data_analysis\n",
            "bachelor-thesis\n",
            "timetable_agent\n",
            "Heterogeneous-robots-protocols\n",
            "students_distribution\n",
            "diploma-work-malikov\n",
            "ROBULAPath\n",
            "zadacha-o-razvozke\n",
            "Diplom2019\n",
            "coursework_2course\n",
            "SpringBootProjectsGenerator\n",
            "tunnel-car-wash-app\n",
            "formulaSearch\n",
            "building_memristive_neuron\n",
            "DipWork\n",
            "ms-creator\n",
            "CarCrashDetection\n",
            "VKRMaketKFU\n",
            "StoryMechanicsGeneration\n",
            "3D_gn_zvuk_diploma\n",
            "FINAL-QUALIFICATION-WORK\n",
            "thesis\n",
            "Master_Thesis_2019\n",
            "city-comm-diploma\n",
            "Dobrokvashina-2019\n",
            "VKR\n",
            "Autotesting\n",
            "SaaSAutoTest\n",
            "AutoTesting\n",
            "qualitis\n",
            "SimulateWeightVR\n",
            "MathFS\n",
            "VKR\n",
            "platform-for-user-testing\n",
            "Diplom\n",
            "DiplomnayaRabota\n",
            "VKR\n",
            "scientometric-indicators\n",
            "mammalian-vocalisation-synthesis\n",
            "Schedule\n",
            "P2PCrowdLanding\n",
            "AnimationUnity\n",
            "ermolaeva\n",
            "analyzer-photos-by-planograms\n",
            "automation-system\n",
            "rrakhimova-diplom\n",
            "Elib_FilTA\n",
            "cdc_demo_project\n",
            "gfiskandarova-diplom\n",
            "MathTest\n",
            "gui-setting-app-doc\n",
            "gui-setting-app\n",
            "OTP\n",
            "graduate-work\n",
            "EmoVideo-thesis\n",
            "highload-testing-app\n",
            "GamingPrototypeGenerator\n",
            "diploma\n",
            "LUT_Table_utility\n",
            "VREngine\n",
            "diplom\n",
            "ui_detection\n",
            "The-Development-Of-Motion-Capture-System\n",
            "NaturalDisasterSimulator\n",
            "course-work-bedrin-11-605\n",
            "robot-lawyer\n",
            "MathMLconvert\n",
            "Diplom\n",
            "upmjs\n",
            "LawDocClassificatorApp\n",
            "BKP-Hayrullin-11504\n",
            "law_dsl\n",
            "designing-empathy-in-virtual-worlds\n",
            "figma-plugin\n",
            "rsjr\n",
            "Diploma\n",
            "graphql-core\n",
            "graphene-neo4j\n",
            "neomodel\n",
            "adaptive-testing-system\n",
            "RPG-Game\n",
            "VideoCategorization\n",
            "diploma\n",
            "rpd-analyzer\n",
            "Presenter\n",
            "project_architecture_generation\n",
            "vk_thesis\n",
            "Lightning_Network\n",
            "Kostyuchenko-2019\n",
            "NativeInterface\n",
            "FormulaSearch\n",
            "distribution\n",
            "BankPortalAggregator\n",
            "AI_via_Neural_Networks\n",
            "K_3\n",
            "LabWork\n",
            "my_course_work\n",
            "course-work-3\n",
            "RPG_game\n",
            "multithreaded-sequence-recovery\n",
            "PhotoTurntable\n",
            "QuizEngine\n",
            "JavaWarrior\n",
            "TicketRecognizer\n",
            "duplicate_finder\n",
            "iaermoshin-diplom\n",
            "SemanticTest\n",
            "CloadRestAPIServicesGeneration\n",
            "Diplom\n",
            "Zalyalutdinov-2019\n",
            "my-awesome-diplom\n",
            "MweExtraction\n",
            "volumetric-cloud\n",
            "vkr\n",
            "RPG_Vakatov\n",
            "photo-editor\n",
            "3-course-work\n",
            "course-work-3-semester\n",
            "robots-battle\n",
            "BlogProject\n",
            "SmartCarSharing\n",
            "HistoryQuiz\n",
            "VideoAnalizer\n",
            "Semester4\n",
            "Marketplace\n",
            "MusEvent\n",
            "ssr-spa-app\n",
            "swarm_hector_quadrotor_monoSLAM\n",
            "stay-in-touch-api\n",
            "ci_cd-methodic-manual\n",
            "JoinAndroifLab\n",
            "microblog-beanPostProcessor-coursework\n",
            "smart-system\n",
            "NLPcourse\n",
            "NLPCourseWork\n",
            "tour-service\n",
            "CompanyPRJ\n",
            "upload-files-to-selectel-cdn-with-spring\n",
            "CourseWork3\n",
            "films\n",
            "SearchSystem\n",
            "mail-sender-service\n",
            "mail-writing-service\n",
            "user-service\n",
            "CourseWork2019\n",
            "health_control_system\n",
            "3-course-work\n",
            "conditional_serializers\n",
            "engineer_server\n",
            "course-work-2019\n",
            "3-course-work\n",
            "avrora-simulation-parking\n",
            "Saitov_Azat_11-707\n",
            "DigitalTwin\n",
            "Join\n",
            "BookCatalogue\n",
            "BookCatalogueJavaFX\n",
            "DrinkQualityDeterminator\n",
            "AnalyticalService\n",
            "coursework-2019-EurekaHRBot\n",
            "uks-mobile\n",
            "passmanager\n",
            "skills_project\n",
            "Shop\n",
            "Course_work\n",
            "FullTextSearch\n",
            "coursework\n",
            "kursach\n",
            "mobile_clients_side\n",
            "server_side\n",
            "diploma\n",
            "metrikano\n",
            "Course_work_2018\n",
            "taiga-back\n",
            "taiga-front\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**звездочки**"
      ],
      "metadata": {
        "id": "ZFCHskUnNoaw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "repositories = [repo['name'] for repo in data]\n",
        "stars = [repo['star_count'] for repo in data]\n",
        "\n",
        "plt.figure(figsize=(8, 8))\n",
        "patches, texts, autotexts = plt.pie(stars, labels=[f'{repo} ({star})' if star != 0 else '' for repo, star in zip(repositories, stars)], autopct='%1.1f%%', startangle=140)\n",
        "for text in texts:\n",
        "    text.set_fontsize(10)\n",
        "for autotext in autotexts:\n",
        "    autotext.set_fontsize(10)\n",
        "plt.axis('equal')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 666
        },
        "id": "l1T3Pvu5MRkF",
        "outputId": "a70e471e-47bc-48e3-f8a5-038794aaa90a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for project in data:\n",
        "    if project.get('forks_count', 0) >= 1:\n",
        "        print(project.get('name', 'fork_count'))"
      ],
      "metadata": {
        "id": "PxK9sdpaTDek"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['repository_size'] = df['statistics'].apply(lambda x: x['repository_size'])\n",
        "\n",
        "size_bins = [0, 500000, 1000000, 1500000, 2000000, float('inf')]\n",
        "size_labels = ['<500KB', '500KB-1MB', '1MB-1.5MB', '1.5MB-2MB', '>2MB']\n",
        "\n",
        "df['repository_size_range'] = pd.cut(df['repository_size'], bins=size_bins, labels=size_labels, right=False)\n",
        "\n",
        "size_counts = df['repository_size_range'].value_counts()\n",
        "\n",
        "plt.figure(figsize=(8, 8))\n",
        "plt.pie(size_counts, labels=size_labels, autopct='%1.1f%%', startangle=140, colors=plt.cm.tab20.colors)\n",
        "plt.title('Distribution of Projects by Repository Size Ranges')\n",
        "plt.axis('equal')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 675
        },
        "id": "WzcfEicx5xHK",
        "outputId": "758b8e66-0efa-47c9-e87e-cad7a92511c2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Проекты, у которых количество коммитов > 100. Наиболее \"интересные\" проекты**"
      ],
      "metadata": {
        "id": "E9rpKs1OAeIA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "projects = data\n",
        "\n",
        "for project in projects:\n",
        "    commit_count = project['statistics']['commit_count']\n",
        "    project_name = project['name']\n",
        "    project_id = project['id']\n",
        "    repository_size = project['statistics']['repository_size']\n",
        "    if commit_count > 100:\n",
        "        print(project_id, project_name)\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "miilgqLW7oC7",
        "outputId": "407065e1-e0b7-44fa-faf6-d4a16d791b9d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "421 visportraits_server\n",
            "330 core\n",
            "344 profile-frontend\n",
            "366 microsimulator-gazebo\n",
            "203 master-thesis\n",
            "254 VASILYEV_VKR_LIRS\n",
            "172 scientometric-indicators\n",
            "231 AnimationUnity\n",
            "98 robot-lawyer\n",
            "184 graphql-core\n",
            "183 graphene-neo4j\n",
            "15 neomodel\n",
            "166 distribution\n",
            "2 taiga-back\n",
            "1 taiga-front\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "with open('web_urls.txt', 'w') as f:\n",
        "    for project in data:\n",
        "        f.write(project['web_url'] + '\\n')"
      ],
      "metadata": {
        "id": "Fpsv5DcmR61O"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "len(df)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9D0J-elzcMoF",
        "outputId": "c84d1c14-4d62-4e89-8042-3a215b6b2806"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "375"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_1 = df[df['description'].str.len() > 1]\n",
        "percentage_of_non_empty_descr = len(df_1) / len(df) * 100\n",
        "percentage_of_empty_descr = (len(df) - len(df_1)) / len(df) * 100\n",
        "print(f\"Количество проектов с описанием в процентах : {percentage_of_non_empty_descr:.2f}%\")\n",
        "print(f\"Количество проектов без описанием в процентах : {percentage_of_empty_descr:.2f}%\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z5fvd2jujFrE",
        "outputId": "6a87432e-6a89-420d-c969-ce97f156529e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Количество проектов с описанием в процентах : 28.27%\n",
            "Количество проектов без описанием в процентах : 71.73%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.pie([percentage_of_non_empty_descr, percentage_of_empty_descr],\n",
        "        labels=['С описанием', 'Без описания'],\n",
        "        autopct='%1.1f%%')\n",
        "\n",
        "plt.title('Проекты с описанием и без описания')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "U6ML6ZukvFRL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 429
        },
        "outputId": "573a4c30-81ef-4182-d6a0-257cb82d8345"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}